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08/14/2023
Conformal Predictions Enhanced Expert-guided Meshing with Graph Neural Networks
Computational Fluid Dynamics (CFD) is widely used in different engineeri...
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06/27/2023
Learning from Invalid Data: On Constraint Satisfaction in Generative Models
Generative models have demonstrated impressive results in vision, langua...
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05/29/2023
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
Generative models have had a profound impact on vision and language, pav...
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05/26/2023
Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings
Generative AI models have made significant progress in automating the cr...
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05/24/2023
Multi-modal Machine Learning for Vehicle Rating Predictions Using Image, Text, and Parametric Data
Accurate vehicle rating prediction can facilitate designing and configur...
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05/18/2023
Counterfactuals for Design: A Model-Agnostic Method For Design Recommendations
We introduce Multi-Objective Counterfactuals for Design (MCD), a novel m...
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05/15/2023
DATED: Guidelines for Creating Synthetic Datasets for Engineering Design Applications
Exploiting the recent advancements in artificial intelligence, showcased...
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05/14/2023
Ship-D: Ship Hull Dataset for Design Optimization using Machine Learning
Machine learning has recently made significant strides in reducing desig...
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05/02/2023
ADVISE: AI-accelerated Design of Evidence Synthesis for Global Development
When designing evidence-based policies and programs, decision-makers mus...
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03/17/2023
Diffusing the Optimal Topology: A Generative Optimization Approach
Topology Optimization seeks to find the best design that satisfies a set...
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02/06/2023
Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design
Deep generative models, such as Variational Autoencoders (VAEs), Generat...
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08/30/2022
LINKS: A dataset of a hundred million planar linkage mechanisms for data-driven kinematic design
In this paper, we introduce LINKS, a dataset of 100 million one degree o...
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08/20/2022
Diffusion Models Beat GANs on Topology Optimization
Structural topology optimization, which aims to find the optimal physica...
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06/14/2022
Towards Goal, Feasibility, and Diversity-Oriented Deep Generative Models in Design
Deep Generative Machine Learning Models (DGMs) have been growing in popu...
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05/06/2022
Design Target Achievement Index: A Differentiable Metric to Enhance Deep Generative Models in Multi-Objective Inverse Design
Deep Generative Machine Learning Models have been growing in popularity ...
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01/25/2022
FRAMED: Data-Driven Structural Performance Analysis of Community-Designed Bicycle Frames
This paper presents a data-driven analysis of the structural performance...
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10/21/2021
Deep Generative Models in Engineering Design: A Review
Automated design synthesis has the potential to revolutionize the modern...
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06/07/2021
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
Engineering design tasks often require synthesizing new designs that mee...
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05/12/2021
A Graph Neural Network Approach for Product Relationship Prediction
Graph Neural Networks have revolutionized many machine learning tasks in...
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03/10/2021
CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis
Modern machine learning techniques, such as deep neural networks, are tr...
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03/10/2021
Range-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis
Typical engineering design tasks require the effort to modify designs it...
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03/10/2021
BIKED: A Dataset and Machine Learning Benchmarks for Data-Driven Bicycle Design
In this paper, we present "BIKED," a dataset comprised of 4500 individua...
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02/15/2021
Self-Organizing Teams in Online Work Settings
As the volume and complexity of distributed online work increases, the c...
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09/15/2020
MO-PaDGAN: Reparameterizing Engineering Designs for Augmented Multi-objective Optimization
Multi-objective optimization is key to solving many Engineering Design p...
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07/07/2020
MO-PaDGAN: Generating Diverse Designs with Multivariate Performance Enhancement
Deep generative models have proven useful for automatic design synthesis...
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06/27/2020
Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems
Metamaterials are emerging as a new paradigmatic material system to rend...
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06/01/2020
METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design
Data-driven design of mechanical metamaterials is an increasingly popula...
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02/26/2020
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs
Deep generative models are proven to be a useful tool for automatic desi...
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02/25/2020
Forming Diverse Teams from Sequentially Arriving People
Collaborative work often benefits from having teams or organizations wit...
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01/30/2018
Creative Exploration Using Topic Based Bisociative Networks
Bisociative knowledge discovery is an approach that combines elements fr...
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09/07/2017
Ranking ideas for diversity and quality
When selecting ideas or trying to find inspiration, designers often must...
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02/23/2017
